Seeing into expertise: a study with the participation of RUDN University professor was the best in the competition of publications on the activities of the investigative bodies of Russia
“The monograph is distinguished by its methodological diversity: it presents all types of forensic examinations, including those that have appeared relatively recently - naming examination, examination of controversial advertising, linguistic examination of extremist materials, tax examination and many others. The work also does not simply describe various types of expert errors but provides a detailed study of their causes and consequences from the point of view of their impact on the effectiveness and reliability of conclusions. The practices of error detection and prevention described in the monograph are addressed to specialists of various profiles, including forensic experts, prosecutors and investigators, lawyers, researchers, and university professors,” of Dmitry Sundukov, Professor, Head of the Department of Forensic Medicine of the RUDN University Institute of Medicine
What errors are the most common in forensic medical examinations today?
The majority of deficiencies and errors arise due to insufficient completeness of research, use of an incomplete set of investigated objects, incorrect selection of an object for laboratory research, violation of research methodology, as well as justification of conclusions by case materials rather than by research results.
One of the most frequent and complex examinations is forensic examination of mechanical trauma. Its task is to determine the cause of death and the nature of bodily injuries, as well as to establish the traumatic instrument, mechanism of trauma and the age of its infliction. Here errors are often caused by the fact that in the detailed description of individual groups of injuries they are considered as independent, not related to each other by the mechanism of formation.
In the investigation of road traffic accidents, forensic medical examination of motor vehicle injuries is conducted. Often errors result from the fact that the expert does not participate in the examination of the vehicle, does not get acquainted with the case materials, does not use all research techniques to identify traces of injuries on the body and clothing. As a result, the conclusions do not always correspond to the actual data.
Another typical error occurs when assessing the age of occurrence of injuries and the sequence of their formation.
Here is an example. Based on the data of histological examination of soft tissues from the traumatisation zone in blunt trauma to the chest with the formation of extensive lung ruptures, complicated by massive blood loss, which led to anaemia of internal organs, it was shown that the chest trauma was inflicted 45-60 minutes before the victim's death. But after repeated forensic medical examination revealed a large volume of haemorrhages in the pleural cavity, massive and infiltrating character of haemorrhages in the soft tissues of the chest, severity and spread of subcutaneous emphysema of the soft tissues of the chest, ‘squeezing’ of the lungs. These factors contradicted the expert's conclusion about the age of the injury. Furthermore, detailed histological study, including the study of internal organs, allowed to establish that the life expectancy of the victim after the injury was not 45-60 minutes, but about 7-9 hours.
Among the authors of the monograph are Rossinskaya E.R., Bodrov N.F., Galyashina E.I., Golikova V.V., Zinin A.M., Ivanova E.V., Klimenko T.V., Kokin A.V., Lebedeva A.K., Mailis N.P., Majorova E.I., Melanich E.V., Neretina N.S., Ogorelkov I.V., Omelyanyuk G.G., Perepechina I.O., Podvolotsky I.N., Saakov T.A., Savitsky A.A., Semikalenova A.I., Slepneva L.I., Sokolova T.P., Starovoitov V.I., Sundukov D.V., Haziev Sh.N., Khatuntsev N.A., Chubina E.A., Shamaev G.P.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.